Analyzing Machine Learning Models with Gaussian Process for the Indoor Positioning System
Joint Authors
Zhu, Zhengwei
Xie, Yunxin
Zhu, Chenyang
Bi, Jia
Jiang, Wei
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-24
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Recently, there has been growing interest in improving the efficiency and accuracy of the Indoor Positioning System (IPS).
The Received Signal Strength- (RSS-) based fingerprinting technique is essential for indoor localization.
However, it is challenging to estimate the indoor position based on RSS’s measurement under the complex indoor environment.
This paper evaluates three machine learning approaches and Gaussian Process (GP) regression with three different kernels to get the best indoor positioning model.
The hyperparameter tuning technique is used to select the optimum parameter set for each model.
Experiments are carried out with RSS data from seven access points (AP).
Results show that GP with a rational quadratic kernel and eXtreme gradient tree boosting model has the best positioning accuracy compared to other models.
In contrast, the eXtreme gradient tree boosting model could achieve higher positioning accuracy with smaller training size and fewer access points.
American Psychological Association (APA)
Xie, Yunxin& Zhu, Chenyang& Jiang, Wei& Bi, Jia& Zhu, Zhengwei. 2020. Analyzing Machine Learning Models with Gaussian Process for the Indoor Positioning System. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195329
Modern Language Association (MLA)
Xie, Yunxin…[et al.]. Analyzing Machine Learning Models with Gaussian Process for the Indoor Positioning System. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1195329
American Medical Association (AMA)
Xie, Yunxin& Zhu, Chenyang& Jiang, Wei& Bi, Jia& Zhu, Zhengwei. Analyzing Machine Learning Models with Gaussian Process for the Indoor Positioning System. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195329
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195329